49817
2006 MDEQ-FEMA Hinds County Lidar Survey
ms2006_mdeq_fema_hindscounty_m2562_metadata
Data Set
Published / External
49401
Lidar - partner (no harvest)
Project
Completed
2013-09-19
This metadata record describes the acquisition and processing of bare earth lidar data, raw point cloud lidar
data, lidar intensity data, and floodmap breaklines consisting of a total of 203 sheets for Hinds County, MS.
The post-spacing for this project is 4-meter. This project was tasked by Mississippi Geographic Information,
LLC (MGI); Work Order No. ED-6. EarthData International, Inc. is a member of MGI and was authorized to undertake
this project in accordance with the terms and conditions of the Professional Services Agreement between MGI and
the Mississippi Department of Environmental Quality (MDEQ), dated February 17, 2004, and in accordance with
MGI Task Order No. 18a.
Original contact information:
Contact Name: Becky Jordan
Contact Org: EarthData International, Inc.
Title: Project Manager
Phone: 301-948-8550 x121
Email: bjordan@earthdata.com
The acquisition, processing, and delivery of bare earth lidar data, raw point cloud lidar data, lidar intensity data,
and floodmap breaklines covering Hinds County, MS was a coordinated effort between EarthData International, Inc.
and MGI, LLC to support MDEM and FEMA flood mapping requirements. Floodmap breaklines are
intended to support DFIRM modeling and update only, and will be delivered to MDEQ for use on the DFIRM
program.
10461
The final LiDAR Report for the Hinds county study area may be accessed at:
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2562/supplemental/ms2006_mdeq_fema_hindscounty.pdf
A footprint of this data set may be viewed in Google Earth at:
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2562/supplemental/ms2006_mdeq_fema_hindscounty.KMZ
Theme
ISO 19115 Topic Category
elevation
Theme
Bare earth
Theme
Bare ground
Theme
DOGAMI
Theme
High-resolution
Theme
Light Detection and Ranging
Office for Coastal Management
Charleston
SC
Data Set
Unknown
Any conclusions drawn from the analysis of this information are not the responsibility of MDEQ, FEMA,
NOAA, the Office for Coastal Management or its partners.
Data Steward
2013-09-19
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Distributor
2013-09-19
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Metadata Contact
2013-09-19
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Point of Contact
2013-09-19
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Publication Date
-90.728886
-90.066405
32.564414
32.048026
Range
2006-04-11
2006-04-12
Yes
Unclassified
This data can be obtained on-line at the following URL:
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=2562
This data set is dynamically generated based on user-specified parameters.
;
None
Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no
longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its
limitations.
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=2562
Customized Download
Create custom data files by choosing data area, product type, map projection, file format, datum, etc.
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2562/index.html
Bulk Download
Simple download of data files.
https://coast.noaa.gov
Online Resource
https://coast.noaa.gov/dataviewer
Online Resource
2016-05-23
Date that the source FGDC record was last modified.
2017-11-14
Converted from FGDC Content Standards for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details.
2018-02-08
Partial upload of Positional Accuracy fields only.
2018-03-13
Partial upload to move data access links to Distribution Info.
Airborne lidar data was acquired at an altitude of 9,500' (2896 m) above mean terrain with a swath width of 7870.12 ft (2398.82 m), which yields an average post spacing of lidar points of no greater than 13.12 ft (4 m). The project was designed to achieve a vertical accuracy of the lidar points at 7.28 in (18.5 cm) root mean square error (RMSE).
The lidar data fully comply with FEMA guidance as published in Appendix A, April, 2003.
The lidar data fully comply with FEMA guidance as published in Appendix A, April 2003. When compared to GPS survey grade points in generally flat non-vegetated areas, at least 95% of the positions have an error less than or equal to 37 cm (equivalent to root mean square error of 18.5 cm if errors were normally distributed).
Cloud Cover: 0
1. EarthData's proprietary software, Checkedb, for verification against ground survey points.
2. Terrascan, for verification of automated and manual editing and final QC of products.
Compliance with the accuracy standard was ensured by the placement of GPS ground control after the acquisition
1. The ground control and airborne GPS data stream were validated through a fully analytical boresight adjustment.
2. The digital terrain model (DTM) data were checked against the project control.
3. Lidar elevation data was validated through an inspection of edge matching and visual inspection for quality (artifact removal).
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2562/supplemental/ms2006_mdeq_hindscounty.pdf
Aerial Acquisition of Lidar Data for Hinds County, MS
2006-04-12
Discrete
2006-04-11
MGI requested the collection of lidar data over Hinds County, MS. In response EarthData International, Inc. acquired the data on April 11 and 12, 2006 using its aircraft with tail number N62912. Lidar data was captured using an ALS50 lidar system, including an inertial measuring unit (IMU) and a dual frequency GPS receiver. An additional GPS receiver was in constant operation over a temporary control point set by EarthData International, Inc. at Hawkins Airport which was later tied into a local network by Waggoner Engineering, Inc. During the data acquisition, the receivers collected phase data at an epoch rate of 1 Hz. The solution from Hinds County, MS was found to be of high integrity and met the accuracy requirements for the project. These accuracy checks also verified that the data meets the guidelines outlined in FEMA's Guidelines and Specifications for Flood Hazard Mapping Partners and Appendix A, section 8, Airborne Light Detection and Ranging (LIDAR) Surveys. Airspeed - 160 knots Laser Pulse Rate - 32900 kHz Field of View - 45 degrees Scan Rate - 18 Hz | Source Geospatial Form: model | Type of Source Media: firewire
Hinds County, Mississippi - Lidar Control
2006-09-18
Discrete
2006-09-18
Waggoner Engineering, Inc., under contract to EarthData International, Inc. successfully established ground control for Hinds County, MS. A total of 16 ground control points in Hinds County, MS were acquired. GPS was used to establish the control network. The horizontal datum was the North American Datum of 1983 (NAD83). The vertical datum was the North American Vertical Datum of 1988 (NAVD88). | Source Geospatial Form: diagram | Type of Source Media: electronic mail system
1
EarthData has developed a unique method for
processing lidar data to identify and remove elevation
points falling on vegetation, buildings, and other
aboveground structures. The algorithms for filtering data
were utilized within EarthData's proprietary software and
commercial software written by TerraSolid. This software
suite of tools provides efficient processing for small to
large-scale, projects and has been incorporated into ISO
9001 compliant production work flows. The following is a
1. The technician performs calibrations on the data set.
2. The technician performed a visual inspection of the
data to verify that the flight lines overlap correctly. The
technician also verified that there were no voids, and that
the data covered the project limits. The technician then
selected a series of areas from the data set and
inspected them where adjacent flight lines overlapped.
These overlapping areas were merged and a process
which utilizes 3-D Analyst and EarthData's proprietary
software was run to detect and color code the differences
in elevation values and profiles. The technician reviewed
these plots and located the areas that contained
systematic errors or distortions that were introduced by the
lidar sensor.
3. Systematic distortions highlighted in step 2 were
removed and the data was re-inspected. Corrections and
adjustments can involve the application of angular
deflection or compensation for curvature of the ground
surface that can be introduced by crossing from one type
of land cover to another.
4. The lidar data for each flight line was trimmed in batch
for the removal of the overlap areas between flight lines.
The data was checked against a control network to
ensure that vertical requirements were maintained.
Conversion to the client-specified datum and projections
were then completed. The lidar flight line data sets were
then segmented into adjoining tiles for batch processing
and data management.
5. The initial batch-processing run removed 95% of points
falling on vegetation. The algorithm also removed the
points that fell on the edge of hard features such as
structures, elevated roadways and bridges.
6. The operator interactively processed the data using
lidar editing tools. During this final phase the operator
generated a TIN based on a desired thematic layers to
evaluate the automated classification performed in step 5.
This allowed the operator to quickly re-classify points from
one layer to another and recreate the TIN surface to see
the effects of edits. Geo-referenced images were toggled
on or off to aid the operator in identifying problem areas.
The data was also examined with an automated profiling
tool to aid the operator in the reclassification.
7. The final bare earth was written to an LAS 1.0 format and
also converted to ASCII.
8. The point cloud data were delivered in LAS 1.0 format.
2006-12-18T00:00:00
2
EarthData utilizes a combination of proprietary and COTS
processes to generate intensity images from the lidar
data. Intensity images are generated from the full points
cloud (minus noise points) and the pixel width is typically
matched to the post spacing of the lidar data to achieve
the best resolution. The following steps are used to
1. Lidar point cloud is tiled to the deliverable tile layout.
2. All noise points, spikes, and wells are deleted out of the
tiles.
3. An EarthData proprietary piece of software, EEBN2TIF
is then used to process out the intensity values of the lidar.
At this point, the pixel size is selected based on best fit or
to match the client specification if noted in the SOW.
4. The software then generates TIF and TFW files for each
tile.
5. ArcView is used to review and QC the tiles before
delivery.
6. The lidar intensity data were delivered in TIF format.
2006-12-18T00:00:00
3
It should be noted that the breaklines developed for use in
the H&H modeling should not be confused with traditional
stereo-graphic or field survey derived breaklines. The
elevation component of the 3D streamlines (breaklines) is
derived from the lowest adjacent bare earth lidar point
and adjusted to ensure that the streams flow downstream.
The best elevation that can be derived for the 3D
streamlines will be the water surface elevation on the date
that the lidar data was acquired. The elevations in the 3D
streamlines will not represent the underwater elevations
for streams due to the fact that lidar data cannot collect
bathymetry information.
Watershed Concepts and EarthData have done
considerable research generating breaklines from lidar
data. Current H&H modeling practices rely heavily on
mass points and breaklines to create a realistic TIN
surface for hydrologic and hydraulic modeling. Lidar data
consists only of points, which are not suited to defining
sharp breaks on terrain. The problem is most pronounced
across stream channels, where lidar is not able to define
the stream banks clearly. Furthermore lidar does not
reflect off water; therefore, no reliable elevation points will
exist within the stream channel itself. The TIN surface
generated from lidar data alone is unsuitable for H&H
modeling.
Watershed Concepts engineers have studied the
sensitivity of the 100-year flood boundary to the definition
of stream channel geometry. The surface created with
both lidar points and breaklines improves channel
definitions for hydraulic cross section takeoffs and better
defines the stream invert. It is not necessary to create
breaklines on the top and bottom of stream banks; minor
modifications to the cross sections and stream inverts can
be made based on field survey data as necessary. In the
100-year flood, most of the flooded cross sectional area
occurs in the overbank; therefore, creating a more refined
channel definition from the lidar data is not cost effective.
The lidar TIN is used simply as the basis for the overbank
definition.
Our research indicates that breaklines are required at the
stream centerline for smaller streams with widths less than
50 feet. For larger streams (widths greater than 50 feet,
breaklines are needed on the left and right water edge
lines. Collection of photography and stereo compilation of
the breaklines is not cost-effective for this purpose.
Watershed Concepts and EarthData have developed
techniques to synthesize 3D breaklines using digital
orthophotos and lidar data. These breaklines can be
digitized in 2D from orthophotos, approximating the stream
bank in areas of significant tree overhang. A bounding
polygon, created from the edge of bank lines, is used to
remove all points within the channel. Automatic processes
assign elevations to the vertices of the centerline based
on surrounding lidar points. The lines are then smoothed
to ensure a continuous downhill flow. Edge-of-bank
vertices are adjusted vertically to match the stream
centerline vertices. A new TIN can then be created from
the remaining lidar points and newly created breaklines.
The new TIN clearly defines the stream channel.
For this project, breaklines were generated in the matter
described above for all streams draining greater than
approximately one square mile. 2D lines defining the
centerline and banks of those streams were manually
digitized into ESRI shape file format from 2005 imagery.
The streamlines were then processed against the bare
earth lidar as described above. The new 3D lines were
then viewed in profile to correct any anomalous vertices or
remove errant points from the lidar DTM, which cause
unrealistic "spikes" or "dips" in the breakline. The 3D
breaklines were delivered in ESRI shapefile format.
2007-01-04T00:00:00
4
The NOAA Office for Coastal Management (OCM) received the files in las format. The files contained LiDAR
elevation and intensity measurements. The data were in Mississippi State Plane West (2301, feet) coordinates and NAVD88
(Geoid03) vertical datum (feet). OCM performed the following processing for data storage and
Digital Coast provisioning purposes:
1. The data were converted from State Plane (2301) coordinates to geographic coordinates.
2. The data were converted from NAVD88 (orthometric) heights to GRS80 (ellipsoid) heights using Geoid03.
3. 8 laz tiles had coordinates falling outside of the header boundary. These tiles were re-tiled to remove any data points falling outside of the header boundary.
4. All laz tiles were received with all points classed as Class 1 (unclassified); the laz tiles were put through lasground.exe (lastools) which uses an algorithm to define which points fall as class 2 (Ground).
5. The data were sorted by time and zipped to laz format.
2013-09-19T00:00:00
gov.noaa.nmfs.inport:49817
Anne Ball
2017-11-15T15:22:30
SysAdmin InPortAdmin
2022-08-09T17:11:36
2022-03-16
OCM Partners
OCMP
1002
Public
No
2022-03-16
1 Year
2023-03-16